Stroke is a leading cause of adult death and disability [Thom T et al., Circulation, 113:e85-151 (2006); WHO, The atlas of heart disease and stroke (2005)]. The diagnosis of ischemic stroke (IS) is made with clinical assessment in combination with brain imaging. However, the diagnosis is not always straightforward, particularly in the acute setting where an accurate, inexpensive and rapid diagnosis is critical to optimally treat patients.
Extensive efforts have been directed toward identifying blood based biomarkers for IS. More than 58 proteins and 7 panels of proteins have been described as biomarkers of IS [Whiteley W et al., Stroke, 39:2902-2909 (2008); Foerch C et al., Neurology, 73:393-399 (2009); Jensen M B et al., Expert Rev Cardiovasc Ther., 7:389-393 (2009)]. RNA expression profiles in the blood have also been described in IS [Tang Y et al., J Cereb Blood Flow Metab., 26:1089-1102 (2006); Moore D F et al., Circulation, 111:212-221 2005]. We previously reported a 29-probe set expression profile predictive of IS [Tang Y et al., J Cereb Blood Flow Metab., 26:1089-1102 (2006)]. This profile required validation in a second cohort, which has been done in the current study. Herein is described a 97-probe set expression profile that differentiates IS from controls, e.g., individuals who are healthy, have vascular risk factors, or who have experienced myocardial infarction. These profiles represent further refinement of gene expression as a diagnostic tool in patients with acute IS.
Ischemic stroke is most commonly classified using the Trial of ORG 10172 in Acute Stroke Treatment (TOAST) criteria, dividing patients into cardioembolic, large vessel, small vessel lacunar, other, and cryptogenic causes [Adams H P, Jr., et al., Stroke, 24:35-41 (1993)]. TOAST criteria improves rater reliability and guides treatment when a known cause can be clearly identified [Goldstein L B et al., Stroke, 32:1091-1098 (2001); Ay H et al., Stroke, 38:2979-2984 (2007)]. However, in many patients the cause of stroke remains unknown or cryptogenic in spite of extensive investigation. Given cryptogenic stroke accounts for approximately 30% of all ischemic strokes, better tools identify the cause of stroke are required [Ionita C C et al., Prev Cardiol., 8:41-46 (2005)].
Blood based biomarkers present a valuable tool to determine the cause of stroke. A number of protein biomarkers have been associated with stroke subtypes. For example, cardioembolic stroke is associated with brain natriuretic peptide and D-dimer; large vessel stroke is associated with C-reactive protein; and small vessel lacunar stroke is associated with homocysteine, ICAM-1, and thrombomodulin [Laskowitz D T et al., Stroke, 40:77-85 (2009); Shibazaki K et al., Intern Med., 48:259-264 (2009); Montaner J et al., Stroke, 39:2280-2287 (2008); Hassan A et al., Brain, 126:424-432 (2003)]. However, biomarkers of ischemic stroke subtype currently lack sufficient sensitivity and specificity to be used in clinical practice. Thus, a combination of biomarkers into a biomarker profile might be one method by which diagnostic specificity and sensitivity can be improved.
The present study determined that gene expression signatures in blood can be used to distinguish cardioembolic from large vessel ischemic stroke, and can be used to predict the cardioembolic and large vessel causes in patients with cryptogenic stroke. The rationale for why changes in blood cell RNA expression occur in ischemic stroke include inflammatory changes associated with acute cerebral ischemia, symptomatic atherosclerosis and thromboembolism [Xu H et al., J Cereb Blood Flow Metab., 28:1320-1328 (2008) 9; Tang Y et al., J Cereb Blood Flow Metab., 26:1089-1102 (2006); Du X et al., Genomics, 87:693-703 (2006)]. Using whole genome microarrays, a 40 gene profile was identified to distinguish cardioembolic stroke from large vessel stroke, and a 37 gene profile was identified to distinguish cardioembolic stroke due to atrial fibrillation from non-atrial fibrillation causes. These genes play roles in inflammation and represent a step toward better determining the cause of cryptogenic stroke.